L06 Scales, Axes, & Legends

Data Visualization (STAT 302)

Overview

The goal of this lab is to explore ways to manage and manipulate scales, axes, and legends within ggplot2.

Datasets

We’ll be using the tech_stocks.rda, corruption.rda, cdc.txt, and a toy dataset.

# load package(s)
library(tidyverse)
library(ggrepel)
library(lubridate)

# load datasets
load("data/corruption.rda")
load("data/tech_stocks.rda")

# Read in the cdc dataset
cdc <- read_delim(file = "data/cdc.txt", delim = "|") |>
  mutate(
    genhlth = factor(
      genhlth,
      levels = c("excellent", "very good", "good", "fair", "poor")
      )
    )

# set seed
set.seed(86420)

# selecting a random subset of size 100
cdc_small <- cdc |> slice_sample(n = 100)

# Generating toy dataset for exercise 2
toy_data <- tibble(
  theta = seq(0, 2 * pi, length.out = 100),
  obs = rnorm(100, sin(theta), 0.1),
  larger_than = if_else(abs(obs) > abs(sin(theta)), "1", "0")
)

Exercise 1

Using the tech_stocks dataset, recreate the following graphic as precisely as possible.

Hints:

• key_glyph
• scales package will be useful
• legend linewidth is 1.3
• legend useful values: 0.75 and 0.85
• Eliminated extra space in horizontal direction

Solution

tech_stocks %>%
  ggplot(aes(date, price_indexed, color = company)) +
  geom_line(key_glyph = "timeseries") +
  scale_y_continuous(
    name = NULL,
    position = "right",
    breaks = seq(0,600, 100),
    labels = scales::label_currency()
  ) +
  theme_minimal() +
  scale_x_date(
    name = NULL,
    expand = c(0,0)
  ) +
  scale_color_discrete(
    name = NULL,
    limits = c("Facebook", "Alphabet", "Microsoft", "Apple")
  ) +
  theme(
    legend.position = "inside",
    legend.position.inside = c(0.75, 0.85)
  ) +
  guides(color = guide_legend(override.aes = list(linewidth = 1.3))) +
  labs(title = "Stock price, indexed")

Exercise 2

Using the corruption.rda dataset, recreate the following graphic as precisely as possible.

Hints:

• Only use 2015 data
• Transparency is 0.6
• "y ~ log(x)"; method "lm"; and color is grey40
• Point size is 3 in legend
• color palette is "Set1"
• Package ggrepel
  • box.padding is 0.6
  • Minimum segment length is 0
  • seed is 9876

Solution

corruption_plot <- corruption %>%
  filter(year == 2015) %>%
  na.omit()

country_highlight <- c("United States", "Singapore", "Japan", "Chile", "Argentina", "China", "Ghana", "Iraq", "Niger")


label_info <- corruption_plot %>%
  filter(country %in% country_highlight)

ggplot(corruption_plot, aes(cpi, hdi)) +
  geom_point(aes(color = region), alpha = 0.6) +
  theme_minimal() +
  geom_smooth(method = "lm", formula = y ~ log(x), color = "grey40", se = FALSE) +
  geom_text_repel(data = label_info, aes(label = country), box.padding = 0.6,
                  min.segment.length = 0,
                  seed = 9876) +
  labs(
    x = "Corruption Perceptions Index, 2015 \n (100 = least corrupt)", 
    y = "Human Development Index, 2015 \n (1.0 = most developed)",
    title = "Corruption and human development (2015)", 
    color = NULL
    ) +
  theme(
    legend.position = "inside",
    legend.position.inside = c(1,0),
    legend.justification = c(1,0)
  ) +
  scale_color_brewer(palette = "Set1") +
  guides(color = guide_legend(override.aes = list(size = 3)))

Exercise 3

Use toy_data to recreate the following graphic as precisely as possible.

Hints:

• Point sizes are 3
• Point colors: #E66100, #5D3A9B
• Point transparency is 0.8
• stat_function() will be useful
  • line size is 1.3 and line color is #56B4E9
• quote() will be useful

Solution

ggplot(toy_data, aes(theta)) +
  geom_point(
    mapping = aes(y = obs, color = larger_than),
    size = 3, alpha = 0.8,
    show.legend = FALSE) +
  stat_function(fun = function(x) sin(x), color = "#56B4E9", size = 1.3) +
  theme_minimal() +
  scale_x_continuous(name = quote(theta)) +
  scale_y_continuous(name = quote(sin(theta))) + 
  scale_color_manual(values = c("#5D3A9B","#E66100"))

Exercise 4

Using cdc_small, construct a scatterplot of weight by height with the following requirements:

• Size of plotting characters should be 3.
• Color and shape should both identify genhlth.
• Only one legend: for both color and shape.
• Legend title should be “General Health?” with a newline starting after general.
• Legend categories should be ordered from excellent (top) to poor (bottom) with each word in category capitalized in the legend.
• Legend should be placed in the lower right-hand corner of the plotting area.
• Color should follow the "Set1" palette.
• Shape should have a solid triangle (17) for excellent, solid circle (19) for very good, an x (4) for poor, an hollow rotated square with an x in it (9) for fair, and a solid square (15) for good.
• height values should be limited between 55 and 80.
• height axis should display every 5th number between 55 and 80 and be appropriately labeled (i.e. 55 in, 60 in, …, 80 in). No axis title is necessary.
• weight values should be limited between 100 and 300.
• weight axis should be trans to log base 10 scale, but still display weights in pounds starting at 100 and displaying every 25 pounds until 300. Must be appropriately labeled (i.e. 100 lbs, 125 lbs, …, 300 lbs). No axis title is necessary.
• Graph title should be CDC BRFSS: Weight by Height.
• Minimal theme.

Solution

ggplot(cdc_small, aes(x = height, y = weight, color = genhlth, shape = genhlth)) +
  geom_point(size = 3) +
  labs(
    color = "General \nHealth?", 
    shape = "General \nHealth?",
    x = NULL,
    y = NULL,
    title = "CDC BRFSS: Weight by Height"
  ) +
  scale_color_brewer(
    palette = "Set1",
    labels = c("Excellent", "Very Good", "Good", "Fair", "Poor")
  ) +
  scale_shape_manual(
    values = c("excellent" = 17,
               "very good" = 19,
               "good" = 15,
               "fair" = 9,
               "poor" = 4),
    labels = c("Excellent", "Very Good", "Good", "Fair", "Poor")) +
  scale_x_continuous(
    limits = c(55,80),
    breaks = seq(55,80, by = 5),
    labels = paste0(seq(55, 80, by = 5), " in")
  ) +
  scale_y_continuous(
    limits = c(100,300),
    trans = 'log10',
    breaks = seq(100,300, by = 25),
    labels = paste0(seq(100, 300, by = 25), " lbs")
  ) +
  theme_minimal() +
  theme(
  legend.position = "inside",
  legend.position.inside = c(1,0),
  legend.justification = c(1,0)
  )